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XCMS / Re: Centroiding of profile-mode DDA data, MS2-level
Last post by Tony -

sure, I tried:
cent_file <- pickPeaks(x = raw_file, refineMz = "descendPeak", signalPercentage = 33, msLevel. = 1, verbose = TRUE)

I receive:
Error in (function (classes, fdef, mtable)  :
  unable to find an inherited method for function ‘pickPeaks’ for signature ‘"missing"’

the raw file is a DDA-sample.
MSn experiment data ("OnDiskMSnExp")
Object size in memory: 2.67 Mb
- - - Spectra data - - -
 MS level(s): 1 2
 Number of spectra: 7205
 MSn retention times: 0:0 - 21:60 minutes
- - - Processing information - - -
Data loaded [Thu Sep 19 13:36:33 2019]
 MSnbase version: 2.11.6
- - - Meta data  - - -
  rowNames:   xyz.mzML
  varLabels: sampleNames
  varMetadata: labelDescription
Loaded from:
protocolData: none
  featureNames: F1.S0001 F1.S0002 ... F1.S7205 (7205 total)
  fvarLabels: fileIdx spIdx ... spectrum (35 total)
  fvarMetadata: labelDescription
experimentData: use 'experimentData(object)'

kind regards
XCMS / Re: Centroiding of profile-mode DDA data, MS2-level
Last post by johannes.rainer -
Hm, that's interesting. Could be that the error comes from smooth, not from pickPeaks. Could you try your code again with only pickPeaks (i.e. skip the smooth step)?

If so, we'll have to add the msLevel. parameter also to the smooth method -

cheers, jo
XCMS / Re: Centroiding of profile-mode DDA data, MS2-level
Last post by Tony -
Hello johannes.rainer/developers,

I was now able to switch to the recent BioC devel (3.10), installed all dev-packages and retested the centroiding of the DDA samples again, with:

>   packageVersion("BiocManager")
[1] ‘1.30.4’
>   packageVersion("MSnbase")
[1] ‘2.11.6’
>   packageVersion("xcms")
[1] ‘3.7.2’

R-Version: 3.6.1, 64 bit, Windows

and used the new parameter "msLevel." with

cent_file <- pickPeaks(smooth(raw_file, method = "SavitzkyGolay", halfWindowSize = 3),
                       refineMz = "descendPeak", signalPercentage = 33, msLevel. = 1)
but still getting:

Writing 1 mzml file.
Saving file xyz.mzML...Error: fun(object@intensity, halfWindowSize = halfWindowSize, ...) : ‘halfWindowSize’ is too large!
In addition: There were 50 or more warnings (use warnings() to see the first 50)
> warnings()
1: In smooth_Spectrum(x, method = match.arg(method), halfWindowSize = halfWindowSize,  ... :
  Negative intensities generated. Replaced by zeros.
2: In smooth_Spectrum(x, method = match.arg(method), halfWindowSize = halfWindowSize,  ... :
  Negative intensities generated. Replaced by zeros.
3: In smooth_Spectrum(x, method = match.arg(method), halfWindowSize = halfWindowSize,  ... :

It seems that the alternative to restrict to msLevel. = 1 is yet (so far) unfortunately not a solution to centroid the DDA runs on MS1 with disregarded MS2. The instrument is a ABSciex Triple ToF 5600.

Thanks again for the work done on this so far and maybe suggestions/workarounds on how to cope with this DDA runs in the future.
kind regards
XCMS Online / MS2 Spectra file in XCMS Online used for MSMS matching
Last post by Mutithu -

I am a new user with XCMS online and have managed to run a few jobs (single, multiple etc).

From my raw data I have MS1 and MS2 scans and the MS2 is used for the identification of the picked feature.

On downloading the finished job there is a file labeled "MS2 Spectra" and in it these are .png files showing the experimental and the reference spectra how they match and the collision energy etc.....

The .png files are numbered and thought this would correspond to the feature idx numbers but seems not to be so.

Any one with an idea of how to link this .png files to the feature idx kindly share the trick.

Kind regards

Conferences and seminars / EMN Webinar 18th September!
Last post by Elena Legrand -
Don't miss it!

Next webinar by Pr Gary Siuzdak "Discovering Metabolites that Alter Physiology, an Omics Perspective"

Click here to register!

Metabolomics and the comprehensive analysis of the metabolome and lipidome has traditionally been pursued with the aim of identifying biomarkers in the diagnosis and prediction of disease. However, the value of metabolomics has been redefined from a simple biomarker identification tool to a technology for the discovery of active drivers of biological processes. It is now clear that the metabolome affects cellular physiology through modulation of other ‘omics’ levels, including the genome, epigenome, transcriptome and proteome. In this presentation, I will focus on our recent progress in using metabolomics to understand how the metabolome influences other omics and, by extension, to reveal the active role of metabolites in physiology and disease. This concept of utilizing metabolomics to perform activity screens to identify biologically active metabolites — which we term activity metabolomics — is already having a broad impact on biology.

Nature Biotechnology 2018, 36 (4), 316-320.
Nature Reviews Molecular Cell Biology 2019 online.

Speaker Details
Gary Siuzdak, Professor and Director of the Center for Metabolomics at The Scripps Research Institute in La Jolla, California ( Gary’s research focuses on developing mass spectrometry-based metabolomic technologies including, XCMS ( and METLIN ( informatic tools, artificial intelligence, metabolomics activity screening and their applications to fundamental biochemistry and therapeutics.
XCMS Online / XCMS error
Last post by pieterventer -
Hello, I am working with Chemstation OPENLAB CDS on a single quad Agilent instrument. My problem is, once i've exported the data as a AIA file and uploaded it as a cdf file on XCMS it gives me the following error "File check & TICs failed".

Any help regarding this error and how to fix it would be greatly appreciated.

XCMS / Re: Vectorized Colors for plotting XChromatogram
Last post by johannes.rainer -
Hi Tony,

excellent suggestion! The parameters are however already vectorized. peakCol, peakBg and peakPch can be either of length 1 or length equal to the number of peaks the XChromatogram/XChromatograms object has peaks (i.e. nrow(chromPeaks(x)) with x being a XChromatogram or an XChromatograms object). You can then define the color for each individual peak (the order of the colors passed along has to match the order of the peaks returned by chromPeaks.

cheers, jo
XCMS / Vectorized Colors for plotting XChromatogram
Last post by Tony -
Dear Develops,

would it be possible for the plotting functions such as:

## XChromatograms {xcms}
## S4 method for signature 'XChromatogram,ANY'
## plot(x, col = "#00000060", lty = 1, type = "l", xlab = "retention time", ylab = "intensity", main = NULL, peakType = c("polygon", "point", "rectangle", "none"), peakCol = "#00000060", peakBg = "#00000020", peakPch = 1, ...)

## plotChromPeakDensity,XCMSnExp-method {xcms}         
## S4 method for signature 'XChromatograms'
##plotChromPeakDensity(object, param, col = "#00000060", xlab = "retention time", main = NULL, peakType = c("polygon", "point", "rectangle", "none"), peakCol = "#00000060", peakBg = "#00000020", peakPch = 1, simulate = TRUE, ...)

to have the arguments:
peakCol = "#00000060", peakBg = "#00000020" (maybe also peakPch = 1) to be able to take vectorized colors like in the argument col?

This would enable mor freedom whilst plotting.

kind regards